{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from GAN_train import GAN_train\n",
    "\n",
    "import tensorflow as tf\n",
    "\n",
    "config = tf.compat.v1.ConfigProto()\n",
    "config.gpu_options.visible_device_list = \"0\"\n",
    "# config.gpu_options.allow_growth = True\n",
    "tf.compat.v1.keras.backend.set_session(tf.compat.v1.Session(config=config))\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    dataset_folder_path = '/recordings_hdd/'\n",
    "    subject = 's000'\n",
    "    gan_train = GAN_train(dataset_folder_path, subject)\n",
    "\n",
    "    gan_train.train(num_epoch=100, batch_size=96, save_interval=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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